BloombergGPT, a 50-billion parameter large language model, promises to revolutionize financial NLP tasks
New York – April 1, 2023 – In a groundbreaking development, Bloomberg has announced the creation of BloombergGPT, a 50-billion parameter large language model (LLM) designed specifically for the financial industry. This state-of-the-art model significantly outperforms similarly-sized open models on financial natural language processing (NLP) tasks without sacrificing performance on general LLM benchmarks.
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Addressing the Complexities of Financial Language
BloombergGPT was developed to tackle the unique complexities and terminology of the financial domain, which often requires a domain-specific model. As a trailblazer in AI, machine learning, and NLP in finance, Bloomberg has been working for over a decade to create a model capable of handling a diverse set of NLP tasks within the financial industry. This new model is expected to improve existing financial NLP tasks such as sentiment analysis, named entity recognition, news classification, and question answering, among others.
BloombergGPT: A Unique Dataset for a Domain-Specific Model
To achieve this milestone, Bloomberg’s ML Product and Research group collaborated with the firm’s AI Engineering team to create one of the largest domain-specific datasets yet. This comprehensive dataset comprises 363 billion tokens of English financial documents collected and maintained by Bloomberg’s data analysts over the past forty years. The dataset was further augmented with a 345 billion token public dataset to create a massive training corpus with over 700 billion tokens.
Combining Finance Data with General-Purpose Datasets
Bloomberg researchers employed a mixed approach to train the model, combining finance data with general-purpose datasets. This innovative method led to best-in-class results on financial benchmarks while maintaining competitive performance on general-purpose LLM benchmarks.
BloombergGPT’s Impressive Performance Across Various NLP Tasks
The BloombergGPT model showcases impressive performance across finance-specific and general-purpose NLP tasks. According to Shawn Edwards, Bloomberg’s Chief Technology Officer, this groundbreaking model “will enable us to tackle many new types of applications while delivering much higher performance out-of-the-box than custom models for each application, at a faster time-to-market.”
New Opportunities and Applications in Finance
Gideon Mann, Head of Bloomberg’s ML Product and Research team, highlighted the importance of high-quality data in the development of the model. He stated, “Thanks to the collection of financial documents Bloomberg has curated over four decades, we were able to carefully create a large and clean, domain-specific dataset to train a LLM that is best suited for financial use cases.”
BloombergGPT & The Future of AI in the Financial Industry
The launch of BloombergGPT marks a significant step towards harnessing the full potential of AI in the financial domain. Its strong performance in finance-specific and general-purpose tasks demonstrates the benefits of developing domain-specific LLMs, paving the way for future innovations in AI and finance.
BloombergGPT appears to be a significant development in the application of AI for the financial industry. By leveraging Bloomberg’s vast archive of financial data and expertise, this LLM is purpose-built to handle the unique complexities and terminology of the financial domain. This innovation will likely help Bloomberg stay at the forefront of AI and NLP applications in finance.
The mixed approach of using both finance-specific and general-purpose datasets allows BloombergGPT to excel in financial tasks while still maintaining competitive performance on general benchmarks. This versatility makes it a valuable tool not only for existing NLP applications but also for exploring new opportunities within the financial industry.
For more information on BloombergGPT, visit the research paper on arXiv: https://arxiv.org/abs/2303.17564.